Job description
About us
ThinkAnalytics, providers of the Emmy® Award Winning Search and Recommendations Engine, is the leading Content Discovery and Viewer Analytics solution worldwide, enabling video service providers, studios, broadcasters, and media companies to deliver personalized experiences to their customers resulting in a significant uplift in viewer engagement, loyalty, and revenue. ThinkAnalytics delivers content discovery and viewer insights to over 80 video service providers, serving over 400 million users in 43 languages with 6 billion+ recommendations per day.
Customers include: HBO, Channel 4, Virgin Media, Deutsche Telekom, Proximus, Tata Sky, Vodafone, DirecTV Latin America, Liberty Global, OTE, Rai, BritBox, Crunchy Roll and many more.
The role
We're looking for ambitious, motivated individuals with a passion for technology to apply for our Summer Internship programme. If successful, you will join us for three months over Summer 2022 and be given the opportunity to work on a project related to our core products. During your internship, you'll be given the opportunity to meet and work within our highly experienced teams, learn new skills and hopefully gain exposure to new tools and technologies whilst being mentored by one of our highly experienced Engineers!
We will provide you an invaluable experience of developing exciting new products with intrinsic value, using leading big data and cloud technologies, working alongside our Data Science team.
We offer our Data Science interns the opportunity to develop products with focus on researching and productionising Machine Learning models as part of their summer dissertation projects .
Additionally, you will have the opportunity to interact and socialise with team members from all levels of the business in a variety of formal and informal settings.
Furthermore, many of our internships result in a firm offer of full-time, permanent employment to return after your graduation.
Requirements
- Students should be in their final year of their MSc (AI/ML-related).
- Students should hold an undergraduate (BSc) degree in a highly quantitative field (maths/comp sci/STEM).
- You should have a genuine interest in technology, and awareness of the current trends in Data Science.
- A knowledge or interest in a selection of the tools & technologies we use, some of which are listed below;
- Python
- ML
- Pandas
- Numpy
- Scikit-learn
- Anaconda
- Git
- Linux
- Apache Spark
- SQL
- Cloud Technologies (e.g. AWS)
- Docker